Field of the Invention
The present invention relates to systems and methods for analyzing computer-mediated communications, including computer generated communications and other communications that have been digitized and fed into a computer.
Description of the Prior Art
Psychological profiling algorithms have been developed based upon the work of Walter Weintraub. Weintraub has identified 14 critical speech categories, as listed in FIG. 1, which are believed by psychologists to reflect the operation of psychological coping mechanisms or defenses. Weintraub's opinion is that the distribution of these variables indicates the distribution of defenses in an individual and provides insight into the individual's psychological state or personality. Weintraub's and his colleague's original research dates from 1964.
This original research demonstrated differences in the distribution of these categories of speech as used by normal persons and persons with different forms of psycho-pathology, including depression, impulsiveness, delusions and compulsiveness. Weintraub profiled and compared political leaders, such as participants in the Watergate matter in 1981. In 1989, he extended his methodology for leadership profiling to the assessment and comparison of United States Presidents, including Eisenhower, Kennedy, Johnson, Nixon, Ford, Carter and Reagan.
Over the past 35 years, Weintraub's algorithms have also been used to analyze the speech and written products of leaders, to develop in-depth psychological profiles of these individuals and comparisons between them. Weintraub has also discussed the possibility of providing computerized portions of his algorithms to expedite the analytical process, but he never did so.
However, Weintraub's algorithms are not known by the public to have been applied to the evaluations of changes in an individual's psychological state over time, to the communications of normal employees in the workplace, to computer-mediated communications, e.g. email and chat, to generating a warning of a potentially dangerous change in an individual's psychological state, to self-monitoring of a person's psychological state, to assessment of the emotional tone of computer-mediated communications or media coverage, or to personnel selection.
The Weintraub algorithms quantify the number of words and relevant events in the speech categories of FIG. 1. The total word count for each category may be multiplied by a corrective figure, which is obtained by dividing 1,000 by the number of words in the sample and rounding off to three decimal places, to provide a normalized basis for comparison.
The Weintraub algorithms may be used to profile the following psychological states:
1. Indicators of Anger—                Increases in the number of:                    words            personal references            negatives            evaluators            statements of feeling            direct references            rhetorical questions            interruptions            I            We                        Decreases in the number of:                    qualifiers            retractors                        
2. Indicators of Anxiety—                Increases in the number of:                    retractors            qualifiers            expressions of feeling            negatives            explainers                        
3. Indicators of Depression—                decreased number of words        increased I        increased me        increased negative key words        increased direct references        increased expressions of feeling        increased evaluators        increased adverbial intensifiers        
4. Indicators of Emotional Withdrawal—                decreased number of words        decreased number of communications        decreased I score        decreased personal references        decreased expressions of feelings        decreased evaluators        
5. Indicators of Rigidity or Lack of Flexibility—                decreased number of qualifiers        decreased number of retractors        decreased we's        increased I's        decreased explainers        increased evaluators        increased adverbial intensifiers        
6. Indicators of Impulsiveness—                increased retractors        increased expressions of feeling        
7. Indicators of Emotional Instability—                increased I-to-We ratio        increased adverbial intensifiers        increased direct references        increased expression of feelings        increased evaluators        
Score Interpretations of Weintraub's psychological profiling algorithms have been suggested as follows:
1. I Scores—                high I score—self-preoccupied        moderate I—healthy ability to commit self in thought and action while maintaining degree of autonomy        low I—avoidance of candor, intimacy, commitment        
2. We Scores—                moderate score—healthy capacity to recognize and collaborate with others        high we+low I—avoidance of intimacy and commitment        
3. Me—                high use reflects dependence and passivity        
4. Negatives—                high scores associated with stubbornness, oppositionality, anger, use of denial as defense mechanism        
5. Qualifiers—                low score—dogmatism—over-certainty, rigidity        high score lack of decisiveness, avoidance of commitment        very high score—anxiety        
6. Retractors—                high score—difficulty adhering to previous decisions, impulsiveness        moderate—mature capacity to reconsider, flexibility, openness to new possibility        very low—dogmatism, rigidity        
7. Direct References—                high scores—difficulty with correspondence or conversation, seeking to distract or manipulate        low or absent—shyness, aloofness, anxiety        
8. Explainers—                high—use of rationalization        low or absent—dogmatism, rigidity        
9. Expressions of Feeling—                low score—aloofness, hesitant to share feelings, trust        high score—insincere, histrionic        
10. Evaluators—                high scores—severe or troubled conscience, psychopathology, anger, dogmatism, rigidity        Low scores—fear of intimacy, lack of commitment        
11. Adverbial Intensifiers—                high scores indicate histrionic personality, exaggeration, rigidity, judgmental        
12. Rhetorical Questions—                increase anger and an effort to control the dialogue        
13. Interruptions—                increased anger and an effort to dominate        
The specialized composite scores with relevance for personal relationships, organizational behavior and leadership remain unpublished but include:                emotionally controlled—low anxiety and depression scores        sensitivity to criticism—high negatives+high explainers+high I+me        accommodating versus rivalrous—low to moderate negatives and moderate to high retractors        oppositional—high negatives score.        controlling in relationships—low score on negatives, feelings, evaluators, and qualifiers        passive vs. active—high me score        planner vs. reactor—high I+we to me ratio        decisiveness—low to moderate qualifiers        unrealistic—high negatives        high need for others—high we        high need for achievement—high I+We, low me, low qualifiers        dependent—high me plus high evaluators, negatives, feelings        well organized—high I+we, low me, low qualifiers, low evaluators, low feelings, low negatives        narcissistic—high negatives+high explainers+high evaluators, high I, low qualifiers        obsessive—high evaluators+high negatives+low retractors, low me, low qualifiers, low feelings        paranoid—high negatives, high explainers, low retractors        loner vs. team player—high I, low we or I to We        
However, Weintraubs algorithms have not been tested or validated for use with computer-mediated communications, media communications, or self-monitoring or in personnel selection. They have not been used to monitor and evaluate changes in emotional state over time, nor have they been applied to the detection and warning of at-risk states. This validation work will be required for a reliable and valid operational system. The current invention also adds multiple variables to the Weintraub categories (e.g. negative and positive feelings, negative and positive evaluators) and uses an original computerized dictionary—presently containing over 1400 words coded for emotional tone. This dictionary is continually updated as data is collected from subject samples.
Beginning in the late 1950's, Gottschalk demonstrated that the arousal associated with psychological events plays an important role in the occurrence of epileptic seizures in children and later (1955) in adults. While working at the National Institute of Mental Health, Gottschalk and his colleagues explored differences in the effects of different forms of stimulation on speech variables, such as rate, frequency, duration of pauses, grammatical categories and parts of speech (Gottschalk and Hambridge, 1955). Later, Gottschalk and his colleagues examined differences in speech between psychotic and non-psychotic patients (Gottschalk, Glessner and Hambridge, 1957). In 1958, Gottschalk conducted a time series analysis of the verbal behavior of a single psychoanalytic patient to determine any possible effects of the therapy (Hambridge and Gottschalk, 1958).
In the 1960's, Gottschalk worked with Dr. Golding Glenser at the University of Cincinnati. This work identified variations in the use of parts of speech by normal individuals according to gender and intelligence (for example, Gleser, Gottschalk and John 1959; Gottschalk and Gleser, 1964). Gottshalk and Gleser (1960) also used their content analysis method to distinguish genuine from pseudo-suicide notes. By the end of the 1960's, Gotschalk and his colleagues added new complexity to their content analysis method by moving from the analysis of individual words to more complex phrases. In 1969, Gottshalk and Gleser described a method for determining an individual's psychological state (anxiety, hostility, alienation, and disorganization) from brief samples of speech (Gottshalk and Gleser 1969). Gottschalk, Wingate and Glesner (1969), have described their content analysis scales in a scoring manual. Since 1969, Gottschalk and colleagues have applied their methods to the study of medical conditions, medications, treatment, and psychological conditions on children, adolescents and adults. This work has been summarized in Gottschalk (1995).
Gottshalk and his colleagues have computerized their content analytical scales in order to make them more efficient and more widely available to other researchers. These efforts are also described in Gottschalk (1995, pgs. 157-160).
Gottschalk and his colleagues have produced a content analytical system that can detect emotional states and changes in emotional states in individuals as a result of a wide range of psychological and medical conditions and treatments. The have also measured changes in these states in individuals over time and designed a computerized version of the system.
However, Gottschalk and his colleagues have not utilized their algorithms regarding communications by normal employees in the workplace, computer-mediated communications, e.g. email and chat, the generation of a warning of a potentially dangerous change in an individual's psychological state, or self-monitoring of a psychological state. Nor have they utilized their approach for the assessment of media images or personnel selection or screening.
Margaret Hermann, over the last 25 years, has used content analysis for psychological profiling. In 1977, Herman (with Thomas Milburn) edited an academic collection entitled “A Psychological Examination of Political Leaders”, (New York Free Press 1977). This text brought together the work of psychologists and political scientists interested in the remote assessment of leadership characteristics utilizing content analysis of the leaders speech and writings. It also contains chapters by political-psychological profilers on the history and different approaches to political psychological content analysis, including Value Analysis (White 1951), Evaluation Assertion Analysis (Osgood 1959), the Psychologic (Shneidman 1961, 1963), General Inquirer (Stone, Dunphy, Smith and Ogilvie 1966), and Mode of Imagery (Winter 1973). Hermann, in 1977, in a chapter entitled, “Vocal Behavior of Negotiators in Periods of High and Low Stress: the 1965-1966 New York City Transit Negotiations,” described a content analytical system that analyzed the psychological state of political leaders involved over time and in different stress states. The collection of content analytical measures drew on the previous work of psychologists, political scientists and others interested in the assessment of emotional states and their changes over time. In another chapter in the same text, she described three content analysis systems designed to assess a leader's beliefs, motives, decision-making and interpersonal style as it might affect their attitude toward foreign aid. These personal characteristics included optimism, cognitive complexity, and humanitarian ideology. The results of the study related variations in these characteristics to the policy positions taken by the leaders examined. Both Herman and her colleagues have refined and expanded the number of personal characteristics derived from content analysis of a leader's speeches or interviews and detailed their effects on a leader's foreign policy orientation and likely political behavior. The personal characteristics of nationalism, belief in one's ability to control events, need for power, need for affiliation, conceptual complexity, self-confidence, distrust of others, and task orientation have been applied to over 100 domestic and foreign political leaders, including heads of states and leaders of revolutionary and terrorist organizations.
Hermann uses scores obtained on a leader for each of the aforementioned eight personal characteristics to classify the leader in terms of six possible foreign policy orientations, including expansionist, active independent, influential, opportunist, mediator and developmental. Each of the orientation types can be expected to differ in world view, political style, decision-making process, manner of dealing with political rivals, and view of foreign policy.
Hermann has designed computerized approaches to her content analytical system. However, complexity of coding required to produce measures for many of the characteristics has limited validity and reliability of the resultant automated process.
In summary, Hermann has designed a content analysis system to assess the motives, beliefs, decision-making and interpersonal style of political leaders. She has applied this system to the in-depth profiling of subjects, comparison with other leaders, and the assessment of the dynamics of leadership groups determined by member differences. She has also used the system to analyze a leader's reaction to distress.
However, Herman has not applied her system to the communications of normal employees in the workplace, to computer-mediated communications, e.g. email and chat, to media communications, to generating a warning of a potentially dangerous change in an individual's psychological state; to self-monitoring of a psychological state or assessment of media images or to management of computer-mediated communications or personnel selection issues.
Another measure of psychological state is described in Mehrabian and Wiener (1966) which is identified herein as “Psychological Distance”. Psychological distance is an emotional state expressed by the speaker toward a target, individual or group. Because the speaker normally unconsciously selects the semantic structures used to calculate psychological distance, it is an excellent measure of “covert” attitude. When a speaker's covert attitude, as measured by psychological distances, is compared with overt content of a speaker's remarks (the number of negative, positive or neutral words associated with the name of an individual or group), it becomes a reliable measure of deception or bluffing. For example, if the overt attitude toward the person or group is positive and the covert attitude is negative, this is an indicator of deception. If the covert attitude towards the group or individual is more positive than the overt attitude, this is an indicator of bluffing.
Psychological distance is scored according to the following guidelines. First, each reference by the speaker to the target is identified. Second, the word structures around the reference to the target are evaluated for the presence or absence of each of the nine conditions below. Third, for each time one of these nine conditions is present, a single score is received. Fourth, for each communication, an average psychological distance score is constructed by taking the number of references to the target divided by the number of points received in the communication across all references to the target. This score is usually between one and nine with the higher score indicating the presence of greater hostility or psychological distance.
Psychological Distance Coding Guideline
1. Spatial: the communicator refers to the object of communication using demonstrative pronouns such as “that” or “those.” E.g. “those people need help” versus “these people need help.”
2. Temporal: the communicator's relationship with the object of communication is either temporally past or future. E.g., “X has been showing me his house” versus “X is showing me his house.”
3. Passivity: the relationship between the communicator and the object of communication is imposed on either or both of them. E.g., “I have to see X” versus “I want to see X.”
4. Unilaterally: the relationship between communicator and the object of communication is not mutually determined. E.g., “I am dancing with X” versus “X and I are dancing.”
5. Possibility: the relationship between the communicator and the object of communication is possible rather than actual. E.g., “I could see X” versus “I want to see X.”
6. Part (of Communicator): only a part, aspect, or characteristic of the communicator is involved in the relationship with the object of communication. E.g., “My thoughts are about X” versus “I am thinking of X.”
7. Object (Part of Object): only a part, aspect, or characteristic of the object of communication is involved in the relationship with the communicator. E.g., “I am concerned about X's future” versus “I am concerned about X.”
8. Class (of Communicator): a group of people who include the communicator is related to the object of communication. E.g., “X came to visit us” versus “X came to visit me.”
9. Class (of Object): the object of communication is related to as a group of objects, which includes the object of communication, e.g., “I visited X and his wife” versus “I visited X.”
However, Mehrabian and Wiener never computerized their system or applied their measure of psychological distance to computer-generated communications, detecting changes in employee groups over time, self-monitoring, assessment of media coverage, or personnel selection issues.
In December 1999, at pages 43-44, in Security Management, it was stated:                “The [inventor's] firm, has developed psycho-linguistic measures sensitive to changes in an employee's psychological state indicative of increased risk. In the case of the employee who abruptly changes tone in his email messages, post hoc use of these measures detected both the employee's initial disgruntlement and the contrast between his overt and covert activities. Had these automated measures been monitored by security, this incident might have been prevented”.        
FIGS. 2-5 illustrate slides presented by the present inventor at conferences on May 12, 1999, Jun. 17, 1999, Jul. 28, 1999, and Oct. 20, 1999 to persons involved with the security industry. The slides illustrate analysis of the electronic mail messages of an actual perpetrator of a computer crime which occurred several months after the e-mail messages were generated. The mean prior values of the number of “negatives”, as illustrated in FIG. 2, the number of “evaluators” as illustrated in FIG. 3, the “number of words per email”, as illustrated in FIG. 4, and the “number of alert phrases” as illustrated in FIG. 5 were compared to the values obtained from analysis of an electronic mail message prior to and associated with the crime in question. The increase over the mean values was discussed as indicating the risk of the criminal activity in question. The slides of FIGS. 2-5 represent the inventor's analysis after the crime occurred of emails of the perpetrator of the crime in question and were not produced at the time of the crime and were not produced by the present invention. As noted above, the categories of evaluators and alert phrases have been modified and expanded since this presentation.
FIG. 6 illustrates a slide presented by the present inventor at the aforementioned conferences analyzing continued covert hostility versus psychological distance over time. As time passed, the criminal whose activities are analyzed above in FIGS. 2-5 deceived his supervisor with “charming pleasantries” as the attack was prepared. Prior art email screening techniques would also have been deceived by the activities of the criminal. As is shown in FIG. 6, a continued high degree of psychological distance was exhibited in emails after the plan of the attack was occurring. This graph was produced by the analysis of the inventor, was not produced by an analysis of the criminal's activity as events unfolded, and was not produced with the present invention.
FIG. 7 illustrates another slide provided by the present inventor at the aforementioned conferences illustrating indicators of psychological distance versus overt attitude consistent with deception. Again, as is seen, the aforementioned conduct of the prior art of FIGS. 2-6 shows a drop in overt hostility from three months to two weeks prior to the crime which deceived the criminal's supervisor, while the analysis, as depicted in FIG. 6, shows a more or less constant continued covert hostility. The graph of FIG. 7 was produced by the present inventor's analysis and was not produced with the present invention.
Email-monitoring software for the securities industry has been developed as a result of a United States Securities and Exchange Commission order that brokerage houses monitor their sales force for illegal sales practices. This software detects key words indicative of potential trading sales violations.
As a result of increased employee use of information technology, non-psychological systems of employee monitoring have emerged which are designed to protect companies from employee misuse or other threats. These systems are operated by companies to monitor employee use of information technology to detect patterns involving unauthorized visits to internet sites, errors in the use of software requiring additional training, and visits by email or other communications to or from unauthorized sites within and external to the organization.
In addition, systems exist to detect occurrence of “keywords” indicative of possible violations of law (the above-referenced security industries practice) and regulations or the existence of possible security violations.
Other systems screen incoming and outgoing communications for the existence of dangerous viruses and/or other destructive content. However, none of these systems currently assesses the psychological tone of computerized communications, the characteristics of authors of these communications, or the psychological state of an employee to generate an indicator of risk, or use these results for the purpose of improved management of communications and relationships. Nor are these systems utilized to evaluate the psychological content of media coverage or as an aid in personnel selection.
In 1984 Jarol Manheim and Robert Albritton published an article in the American Political Science Review entitled “Changing National Images: International Public Relations and Media Agenda Setting.” In the article the authors proposed the assessment of the media image of a nation according to several criteria, including mean insertions per month (the number of times the nation is mentioned in the media) and the percent of all insertions which were positive (page 654). This scheme was used to determine the impact of the efforts of public relations firms on the media image of target nations by tracking the number of insertions and the percent of insertions which were positive before and after the public relations firm's efforts.
The current invention utilizes a related scheme to measure the quantity and emotional tone of communications. However, in addition to the number of communications, the current invention utilizes the length, frequency per time period and other characteristics of the communications. In addition to the percent of insertions which are positive, the current invention initially examines the percent which are positive and negative. Instead of coding the percent positive by observation and hand, the current invention automatically codes the content of the communications in a more complex fashion utilizing psychological content analysis categories such as negative and positive feelings, negative and positive evaluators and negatives. The user can then examine the actual content associated with this coding to determine the content associated with the emotional tone. In addition, the authors never applied their scheme to the computerized communications of individuals, changes in the emotional tone of these communications over time, support for managing these media- and computer-based relationships, monitoring and assessing potential risk from an individual's psychological state, or personnel selection processes.